Machine Learning Practical: 6 Real-World Applications
Machine Learning – Get Your Hands Dirty by Solving Real Industry Challenges with Python
What you’ll learn
You will know how a real data science project looks like
You will be able to include these Case Studies in your resume
You will be able better market yourself as a Machine Learning Practitioner
You will feel confident during a Data Science interview
You will learn how to chain multiple ML algorithms together to achieve the goal
You will learn the most advanced Data Visualization techniques with Seaborn and Matplotlib
You will learn Logistic Regression
You will learn L1 Regularization (Lasso)
You will learn Random Forest Classifier
You need to know Python (Machine Learning A-Z level is enough) in order to complete this course.
You need to know how to set up your working environment (Anaconda, Jupyter Notebook, Spyder)
This should not be your first Machine Learning course. You need to understand the main concepts.
In this course, we will also cover Deep Learning Techniques and their practical applications.
So as you can see, our goal here is to really build the World’s leading practical machine learning course.
If your goal is to become a Machine Learning expert, you know how valuable these real-life examples really are.
They will determine the difference between Data Scientists who just know the theory and Machine Learning experts who have gotten their hands dirty.
So if you want to get hands-on experience that you can add to your portfolio, then this course is for you.
Enroll now and we’ll see you inside.
Who this course is for:
- Data Science and Machine Learning enthusiasts who want to understand how real data science projects look like.
- Anyone with Machine Learning and Python knowledge who wants to practice their skills
Size: 4.04 GB